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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Test, deploy, and manage agents | 20–25% | - Test and validate agent performance
|
| Topic 2: Build and extend agents in Copilot Studio | 40–45% | - Implement advanced capabilities
|
| Topic 3: Plan and configure agent solutions | 30–35% | - Configure agent foundations
|
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NEW QUESTION # 127
An agent needs to call an external REST API that isn't available as a pre-built connector, and the API requires OAuth 2.0 authentication. What should you create?
Answer: C
NEW QUESTION # 128
You run multiple evaluation tests for an agent in Copilot Studio before expanding user access.
You observe the following about the evaluation results:
Each evaluation case is reported as meeting or missing the expected response.
Some evaluation cases fail repeatedly across several runs.
Each run displays the expected response and the response generated by the agent.
You need to interpret what the evaluation results reveal.
What should you conclude based on each interpretation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 129
Case Study 1 - Blue Yonder Airlines
Background
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and international flights. The company serves millions of passengers annually through its website, mobile app, and call centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels - web chat, mobile app, and Microsoft Teams (for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human agents when needed.
The project is led by a cross-function team:
- Product manager: Defines requirements and success metrics.
- Lead agent author: Designs topics, intents, and generative behavior.
- Flow designers: Build agent flows and integrations.
- IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment
Channels
Public website: Embedded web chat
Mobile app: In-app chatbot
Microsoft Teams: Internal support agent access
Identity and access
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements
Omnichannel support
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must also support internal staff.
Self-service capabilities
The agent must handle common inquiries such as:
- Flight status
- Booking and rebooking
- Loyalty program questions
- Travel policies and baggage rules
Human escalation
If the agent cannot resolve an issue or the user requests help, it must:
- Escalate to a human agent.
- Transfer the conversation transcript and relevant context.
- Redact any sensitive personal data before escalation.
Knowledge integration
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A topics for each document.
Performance metrics
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs
CSAT: ≥85% for AI-handled interactions
Technical requirements
Platform constraints
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must be avoided.
Monitoring and maintenance
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Topics, flows, and knowledge sources must be updated as policies or systems evolve.
Issues and constraints
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents.
Large files must be split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations.
Prompt modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across channels.
Problem statement
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio. The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise systems, and support both anonymous and authenticated users. It must adhere to strict data protection and Responsible AI standards while improving customer service efficiency and satisfaction.
You need to ensure that every AI-generated response from the agent in Copilot Studio includes a disclaimer that complies with the company's security and governance policies.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: C,D
Explanation:
[B]
Using prompt modification in the Generative Answers node settings is an excellent and highly effective strategy for embedding compliance disclaimers into your agent's responses.
[A]
Adding a mandatory disclaimer to your greeting message is the best practice for agent governance. You can enforce this by configuring your Greeting System Topic and adding formal
"Output Rules" to the agent's core instructions.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/nlu-boost-node
https://www.reddit.com/r/copilotstudio/comments/1pje5fy/how_do_you_handle_ai_disclaimers_in_copilot/
NEW QUESTION # 130
A company is configuring an agent in Copilot Studio that uses a generative answers node inside multiple topics.
The company requires responses to meet the following requirements.
* Must use an executive summary format
* Must apply only within a specific topic.
* Must continue using configured knowledge sources.
* Must comply with connector security controls.
You need to configure a custom prompt to meet the formatting requirements Solution: Create a custom prompt tool in the specific topic that instructs the model to respond using an executive-summary structure.
Does the solution meet the goal?
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: A separate custom prompt tool that merely requests an executive-summary structure does not, by itself, guarantee that the existing generative answers node and its configured knowledge sources remain in the response path. Prompt tools have their own inputs, knowledge configuration, model settings, and completion behavior. If the tool is invoked independently, it can generate correctly formatted text without using the sources selected for the topic
' s generative answer, which violates a stated requirement. The safer design is to keep the generative answers node and apply topic-specific custom instructions or prompt modification to that node, or explicitly pass its grounded output into a downstream formatting prompt with a controlled contract. Connector security remains enforced by the underlying connections and data policies; wording in a prompt cannot override those controls.
Therefore, the proposed solution is incomplete and does not meet the goal as written. Testing should confirm not only the output format but also the sources used and the identity under which any connector retrieval occurred. Study Guide alignment: Plan and configure agent solutions > Configure topics > Configure advanced agent responses with custom prompts and custom knowledge sources.
NEW QUESTION # 131
An agent in Copilot Studio must retrieve real-time data from an external system that exposes a REST API.
The API returns structured JSON data and requires authentication.
The agent must call the API during conversations to fulfill user requests.
The agent must retrieve real-time data from the external system by calling an authenticated REST API during a conversation.
The solution must use a supported mechanism that executes the REST API call and the call must be explicitly configured to run at runtime.
You need to determine which approaches add the REST API to the agent.
Which two solutions meet the goal? Each correct answer is a complete solution.
NOTE: Each correct selection is worth one point.
Answer: C,D
Explanation:
[A] Configure an HTTP action and invoke it from a topic during the conversation.
This is a correct and supported solution.
You can fulfill this requirement directly within Microsoft Copilot Studio by configuring an HTTP Request node (HTTP action) inside a topic.
Real-Time Execution: The HTTP action is explicitly executed at runtime during the live conversation when the specific topic is triggered.
Native Authentication Support: The HTTP Request node allows you to securely pass authentication tokens, API keys, or custom credentials directly within the request headers.
Handles Structured JSON: The node natively supports standard REST methods (GET, POST, PATCH, PUT, DELETE) and can ingest structured JSON data, allowing you to parse and store the returned values into agent variables for use later in the conversation.
[C] Add the REST API as a tool and call it either by using a topic or agent instruction.
Depending on how your agent architecture is managed, you could also fulfill this requirement using these alternative methods:
*-> REST API Tools (OpenAPI Plugins): You can upload an OpenAPI specification directly into Copilot Studio to register the REST API as a native REST API tool/action.
* Power Automate Flows: You can invoke a Power Automate cloud flow from a topic, using the HTTP connector inside the flow to retrieve and pass back the JSON data.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/agent-extend-action-rest-api
NEW QUESTION # 132
......
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